Transcriptome data modeling for targeted plant metabolic engineering

The massive data generated by omics technologies require the power of bioinformatics, especially network analysis, for data mining and doing data-driven biology. Gene coexpression analysis, a network approach based on comprehensive gene expression data using microarrays, is becoming a standard tool for predicting gene function and elucidating the relationship between metabolic pathways. Differential and comparative gene coexpression analyses suggest a change in coexpression relationships and regulators controlling common and/or specific biological processes. In conjunction with the newly emerging genome editing technology, network analysis integrated with other omics data should pave the way for robust and practical plant metabolic engineering.

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► Network analysis is essential for data mining of omics-based large-scale data sets.
► Gene coexpression analysis is useful for prediction of gene function.
► Comparative network analysis can reveal common and unique plant metabolic pathways.
► Novel genome editing tools facilitate rational metabolic engineering.